An optimisation based Moving Horizon Estimation with application to localisation of Autonomous Underwater Vehicles

Engineering

• Accuracy 16%
• Algorithm 83%
• Applications 50%
• Autonomous Underwater Vehicle 50%
• Computational Complexity 16%
• Computer Simulation 16%
• Cooperative 16%
• Discrete-Time Systems 16%
• Extended Kalman Filter 16%
• Filters 50%
• Localisation 100%
• Localization Accuracy 16%
• Localization Problem 16%
• Maximum a Posteriori 16%
• Multiple Sensor 16%
• Nonlinear Discrete 16%
• Observability 33%
• Optimization 66%
• Payload 16%
• Physical Constraint 16%
• Range Measurement 16%
• Requirements 16%
• Simulators 16%
• Solving Optimization Problem 16%
• Sufficient Condition 16%
• Surfaces 16%

Computer Science

• Accuracy 16%
• And-States 16%
• Application 50%
• Contexts 16%
• Data Fusion 16%
• Discrete Time System 16%
• Extended Kalman Filter 16%
• Localization Problem 16%
• Moving Horizon Estimation 33%
• Multiple Sensor 16%
• Numerical Simulation 16%
• Optimization 66%
• Physical Constraint 16%
• Relationships 16%
• Relative Advantage 16%
• Sufficient Condition 16%